set drop_last=false

configs/det/det_mv3_db.yml

@@ -9,6 +9,7 @@ Global:
   eval_batch_step: 5000
   train_batch_size_per_card: 16
   test_batch_size_per_card: 16
+  drop_last: false
   image_shape: [3, 640, 640]
   reader_yml: ./configs/det/det_db_icdar15_reader.yml
   pretrain_weights: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/

configs/det/det_mv3_east.yml

@@ -9,6 +9,7 @@ Global:
   eval_batch_step: 5000
   train_batch_size_per_card: 16
   test_batch_size_per_card: 16
+  drop_last: false
   image_shape: [3, 512, 512]
   reader_yml: ./configs/det/det_east_icdar15_reader.yml
   pretrain_weights: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/

configs/det/det_r50_vd_db.yml

@@ -10,6 +10,7 @@ Global:
   train_batch_size_per_card: 8
   test_batch_size_per_card: 16
   image_shape: [3, 640, 640]
+  drop_last: false
   reader_yml: ./configs/det/det_db_icdar15_reader.yml
   pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/
   save_res_path: ./output/det_db/predicts_db.txt

configs/det/det_r50_vd_east.yml

@@ -10,6 +10,7 @@ Global:
   train_batch_size_per_card: 8
   test_batch_size_per_card: 16
   image_shape: [3, 512, 512]
+  drop_last: false
   reader_yml: ./configs/det/det_east_icdar15_reader.yml
   pretrain_weights: ./pretrain_models/ResNet50_vd_ssld_pretrained/
   save_res_path: ./output/det_east/predicts_east.txt

configs/rec/rec_chinese_lite_train.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 320]
   max_text_length: 25
   character_type: ch

configs/rec/rec_icdar15_train.yml

@@ -8,14 +8,14 @@ Global:
   save_epoch_step: 300
   eval_batch_step: 500
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en
   loss_type: ctc
   reader_yml: ./configs/rec/rec_icdar15_reader.yml
-  pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy
+  pretrain_weights:
   checkpoints:
   save_inference_dir:
   infer_img:

configs/rec/rec_mv3_none_bilstm_ctc.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_mv3_none_none_ctc.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_mv3_tps_bilstm_attn.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_mv3_tps_bilstm_ctc.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_r34_vd_none_bilstm_ctc.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_r34_vd_none_none_ctc.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_r34_vd_tps_bilstm_attn.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

configs/rec/rec_r34_vd_tps_bilstm_ctc.yml

@@ -8,8 +8,8 @@ Global:
   save_epoch_step: 3
   eval_batch_step: 2000
   train_batch_size_per_card: 256
-  drop_last: true
   test_batch_size_per_card: 256
+  drop_last: false
   image_shape: [3, 32, 100]
   max_text_length: 25
   character_type: en

ppocr/data/det/dataset_traversal.py

@@ -32,6 +32,7 @@ class TrainReader(object):
         self.num_workers = params['num_workers']
         self.label_file_path = params['label_file_path']
         self.batch_size = params['train_batch_size_per_card']
+        self.drop_last = params['drop_last']
         assert 'process_function' in params,\
             "absence process_function in Reader"
         self.process = create_module(params['process_function'])(params)
@@ -61,6 +62,7 @@ class TrainReader(object):
                 if len(batch_outs) == self.batch_size:
                     yield batch_outs
                     batch_outs = []
+            if not self.drop_last:
                 if len(batch_outs) != 0:
                     yield batch_outs
 

ppocr/data/rec/dataset_traversal.py

@@ -42,6 +42,7 @@ class LMDBReader(object):
         self.max_text_length = params['max_text_length']
         self.mode = params['mode']
         self.drop_last = False
+        self.tps = False
         if "tps" in params:
             self.tps = True
         if params['mode'] == 'train':
@@ -180,6 +181,9 @@ class SimpleReader(object):
         self.max_text_length = params['max_text_length']
         self.mode = params['mode']
         self.infer_img = params['infer_img']
+        self.tps = False
+        if "tps" in params:
+            self.tps = True
         self.drop_last = False
         if params['mode'] == 'train':
             self.batch_size = params['train_batch_size_per_card']
@@ -192,7 +196,7 @@ class SimpleReader(object):
             process_id = 0
 
         def sample_iter_reader():
-            if self.infer_img is not None:
+            if self.mode != 'train' and self.infer_img is not None:
                 image_file_list = get_image_file_list(self.infer_img)
                 for single_img in image_file_list:
                     img = cv2.imread(single_img)
@@ -201,7 +205,9 @@ class SimpleReader(object):
                     norm_img = process_image(
                         img=img,
                         image_shape=self.image_shape,
-                        char_ops=self.char_ops)
+                        char_ops=self.char_ops,
+                        tps=self.tps,
+                        infer_mode=True)
                     yield norm_img
             else:
                 with open(self.label_file_path, "rb") as fin: